FOLLOW US

Algorithm Enables Faster Analysis of Medical Images

This technique makes the process of comparing 3D scans up to 1,000 times faster.

Massachusetts Institute of Technology, Cambridge

Medical image registration is a common technique that involves overlaying two images, such as magnetic resonance imaging (MRI) scans, to compare and analyze anatomical differences in great detail. If a patient has a brain tumor, for instance, doctors can overlap a brain scan from several months ago onto a more recent scan to analyze small changes in the tumor's progress.

A machine-learning algorithm can register brain scans and other 3D images more than 1,000 times more quickly using novel learning techniques. (MIT)

This process, however, can often take two hours or more, as traditional systems meticulously align each of potentially a million pixels in the combined scans. A machine-learning algorithm was developed that can register brain scans and other 3D images more than 1,000 times more quickly using novel learning techniques. The algorithm works by “learning” while registering thousands of pairs of images. In doing so, it acquires information about how to align images and estimates some optimal alignment parameters. After training, it uses those parameters to map all pixels of one image to another, all at once. This reduces registration time to a minute or two using a normal computer, or less than a second using a GPU with comparable accuracy to state-of-the-art systems. The algorithm is “unsupervised,” meaning it doesn't require additional information beyond image data.

MRI scans are basically hundreds of stacked 2D images that form massive 3D images called “volumes,” containing a million or more 3D pixels called “voxels.” Therefore, it's very time-consuming to align all voxels in the first volume with those in the second. Moreover, scans can come from different machines and have different spatial orientations, meaning matching voxels is even more computationally complex. This process becomes particularly slow when analyzing scans from large populations.

The algorithm has a wide range of potential applications in addition to analyzing brain scans, including lung imaging. The algorithm could also pave the way for image registration during operations. Various scans of different qualities and speeds are currently used before or during some surgeries, but those images are not registered until after the operation. When resecting a brain tumor, for instance, surgeons sometimes scan a patient's brain before and after surgery to see if they've removed all the tumor. If any part of the tumor remains, the patient must go back to the operating room.

For more information, contact Abby Abazorius at This email address is being protected from spambots. You need JavaScript enabled to view it.; 617-253-2709.

Tech Briefs Media Group

Sign In

By submitting your personal information, you agree that Tech Briefs Media Group and carefully selected industry sponsors of this content may contact you and that you have read and agree to the Privacy Policy.